Building Machine Learning Powered Applications: Going from Idea to Product (English Edition) Kindle电子书
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|页数 : 共367页||更先进的排版模式: 已启用||快速翻书: 已启用|
- 文件大小 : 13590 KB
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- 纸书页数 : 367页
- 出版社 : O'Reilly Media (2020年1月21日)
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- 语种： : 英语
- ASIN : B0842ZD3Y7
- 亚马逊热销商品排名: 商品里排第262,028名Kindle商店 (查看商品销售排行榜Kindle商店)
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美国亚马逊： 10 条评论
Exactly What I Was Looking For2020年2月27日 - 已在美国亚马逊上发表
This book is NOT an overly technical book. The way I read it, it's a book that's centered around the lessons the author, Emmanuel , learned during his time as a data scientist/ML engineer. He formats these lessons in such a way that makes the book extremely easy to read and grasp. As a newly-hired data scientist who has been charged with created the company's anomaly detection application, this book will serve me well!
LIghtweight2020年8月6日 - 已在美国亚马逊上发表
I don't think the author has built a machine-learning powered application. This book is extremely lightweight at a little over 200 pages and is too high-level to have any practicality. The content is just an odd assortment of stuff with bizarre sidebars on transfer learning and code snippets with no cohesiveness. The chapter on deployment is exactly ten pages long and is a big nothing burger. I don't even recommend this book for a beginner because it will confuse them.
I strongly recommend this book for anyone managing a DS or MLE team.2020年8月26日 - 已在美国亚马逊上发表
I've met a lot of people who would say they are well aware of the contents of this book and that they would have nothing to learn from reading it. But, it amazes me how many times I've seen those people spin up projects and completely ignore the steps they claim to know. If you're managing a team, I think this should be required reading. "Building Machine Learning Powered Applications: Going from Idea to Product" helps to crystalize the best practices that are, all too often, neglected at fast-moving startups and on rapid-prototyping teams.
introductory and superficial2020年8月5日 - 已在美国亚马逊上发表
This book is introductory and superficial. Probably good for aspiring/junior data scientists, but not very interesting for more experienced practitioners.
Highly recommend2020年2月23日 - 已在美国亚马逊上发表
Fantastic book for those interested in ML! Very well written and great for those looking to take their skills to the next level!